A firefly-based particle filter technique for system state estimation and battery RUL prediction

被引:1
作者
Ahwiadi, Mohamed [1 ]
Wang, Wilson [1 ]
机构
[1] Lakehead Univ, Dept Mech & Mechatron Engn, Thunder Bay, ON P7B 5E1, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
particle filter; system state estimation; firefly algorithm; battery remaining useful life prediction; particle degeneracy; impoverishment; REMAINING USEFUL LIFE; PROGNOSTICS;
D O I
10.1088/1361-6501/ad8fc3
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Cross-coupling among the fundamental degrees of freedom in solids has been a long-standing problem in condensed matter physics. Despite its progress using predominantly three-dimensional materials, how the same physics plays out for two-dimensional materials is unknown. Here, we show that using 31 P nuclear magnetic resonance (NMR), the van der Waals antiferromagnet NiPS3 undergoes a first-order magnetic phase transition due to the strong charge-spin coupling in a honeycomb lattice. Our 31 P NMR spectrum near the N & eacute;el ordering temperature TN = 155 K exhibits the coexistence of paramagnetic and antiferromagnetic phases within a finite temperature range. Furthermore, we observed a discontinuity in the order parameter at TN and the complete absence of critical behavior of spin fluctuations above TN, decisively establishing the first-order nature of the magnetic transition. We propose that a charge stripe instability arising from a Zhang-Rice triplet ground state triggers the first-order magnetic transition. Keywords: magnetic van der Waals, nuclear magnetic resonance, Zhang-Rice exciton, first-order magnetic transition
引用
收藏
页数:11
相关论文
共 29 条
[1]   An Adaptive Particle Filter Technique for System State Estimation and Prognosis [J].
Ahwiadi, Mohamed ;
Wang, Wilson .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2020, 69 (09) :6756-6765
[2]   An Enhanced Mutated Particle Filter Technique for System State Estimation and Battery Life Prediction [J].
Ahwiadi, Mohamed ;
Wang, Wilson .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2019, 68 (03) :923-935
[3]   A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking [J].
Arulampalam, MS ;
Maskell, S ;
Gordon, N ;
Clapp, T .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2002, 50 (02) :174-188
[4]   Comprehensive Remaining Useful Life Prediction for Rolling Element Bearings Based on Time-Varying Particle Filtering [J].
Cui, Lingli ;
Li, Wenjie ;
Wang, Xin ;
Zhao, Dezun ;
Wang, Huaqing .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 71
[5]   A Particle Filter for Dynamic State Estimation in Multi-Machine Systems With Detailed Models [J].
Cui, Yinan ;
Kavasseri, Rajesh .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2015, 30 (06) :3377-3385
[6]   A comprehensive review of firefly algorithms [J].
Fister, Iztok ;
Fister, Iztok, Jr. ;
Yang, Xin-She ;
Brest, Janez .
SWARM AND EVOLUTIONARY COMPUTATION, 2013, 13 :34-46
[7]   Auxiliary Particle Filtering-Based Estimation of Remaining Useful Life of IGBT [J].
Haque, Moinul Shahidul ;
Choi, Seungdeog ;
Baek, Jeihoon .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2018, 65 (03) :2693-2703
[8]   Prognostics and health management: A review from the perspectives of design, development and decision [J].
Hu, Yang ;
Miao, Xuewen ;
Si, Yong ;
Pan, Ershun ;
Zio, Enrico .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2022, 217
[9]   Particle filter-based prognostics: Review, discussion and perspectives [J].
Jouin, Marine ;
Gouriveau, Rafael ;
Hissel, Daniel ;
Pera, Marie-Cecile ;
Zerhouni, Noureddine .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2016, 72-73 :2-31
[10]   Remaining useful life prediction of lithium-ion batteries using EM-PF-SSA-SVR with gamma stochastic process [J].
Keshun, You ;
Guangqi, Qiu ;
Yingkui, Gu .
MEASUREMENT SCIENCE AND TECHNOLOGY, 2024, 35 (01)